Joe Fitzpatrick is an Assistant Lecturer at the Department of Digital Arts and Media within the Limerick School of Art and Design. His research focuses on auditory scene analysis, sonification techniques, and algorithmic composition. He explores how auditory displays can enhance data interpretation through psychoacoustic principles and multimodal interfaces. Key research interests include the perceptual congruency of auditory line charts, harmonic variance in auditory graphs, and data-driven approaches to musical composition. His work bridges computer science and artistic media, emphasizing user-centered design and interdisciplinary applications. Publications span topics like sonification design, auditory graph analysis, and algorithmic music systems. While no awards or grants are explicitly listed, his contributions to conferences such as Sound and Music Computing (SMC) and Audio Mostly highlight active engagement in academic discourse.
Beatriz Martinez-Pastor is an Assistant Professor in the School of Civil Engineering at University College Dublin (UCD). Her roles include teaching and coordinating modules such as Transport Modelling, Transportation Engineering, and Civil Engineering Design Graphics. She holds a PhD from Trinity College Dublin and an MSc from the University of Cantabria, complemented by a Professional Certificate in University Teaching and Learning from UCD. Her research focuses on transport network resilience, particularly in quantifying system behavior under disruptions like natural disasters and cyber-physical attacks. Key areas include probabilistic analysis, data-driven modeling, and infrastructure vulnerability assessment. She has contributed to frameworks for evacuation planning, cyber-physical system robustness, and flood adaptation strategies. Her articles highlight advancements in accident analysis methods, cyber-physical resilience, and multi-objective optimization for disaster scenarios. Notable grants include the Horizon Europe-funded SETO project (2023–2026) and CAPABLE (2023–2024), addressing transport enforcement and community resilience. Martinez-Pastor has received the Excellence Award (2019) and serves on committees like the TRB Committee on Critical Infrastructures. Her work bridges academic research with practical applications in disaster management, cybersecurity, and sustainable infrastructure.
Professor Mark Roantree leads the Data Engineering & Governance research challenge at Dublin City University's Insight Centre for Data Analytics. With €3.5M+ secured funding and 150+ publications, his multidisciplinary research develops analytical solutions for climate science, agriculture, health, and human performance. He has graduated 23 research students and currently supervises PhDs in graph analytics, climate modeling, and health data systems. Research applications include: Physics-informed neural networks for ecological modeling Sports analytics using wearable sensors Healthcare data integration for chronic diseases FAIR climate data management
Martin Crane is Professor and Head of School at Dublin City University School of Computing. Funded Investigator in ADAPT Centre, with PhD in Mechanical Engineering from Trinity College Dublin. Research spans computational finance, complex systems modeling, and high-performance computing applications. Key research areas: Time series analysis in finance/biology Complex systems in finance, immunology, and lifelogging Wavelet methods for market analysis Parallel computing for large-scale simulations Current projects examine cryptocurrency dynamics, healthcare analytics, and brain tumor segmentation using deep learning. Leads FinTech Fusion initiative exploring financial technology applications. Authored significant works on random matrix theory filters for portfolio optimization and agent-based HIV modeling.
Alessandra Mileo is Associate Professor and Data Science Programme Chair at Dublin City University's Faculty of Engineering and Computing. As a Principal Investigator at the Insight SFI Research Centre for Data Analytics, her research focuses on neurosymbolic AI, explainability, and representation learning. Education includes an M.Sc. and Ph.D. in Computer Science from the University of Milan. Current research investigates methods combining knowledge-driven and data-driven AI approaches to enhance explainability and reduce bias in machine learning systems. Research leadership includes EU projects like CityPulse (IoT stream processing) and industry collaborations on Internet of Everything infrastructures. Teaches data science courses and supervises multiple PhD students.
Dr. Marija Bezbradica serves as Associate Professor and COMBUS Programme Board Chair at Dublin City University's School of Computing. Her research bridges computational finance, educational analytics, and complex systems modeling. Key research areas include financial risk modeling using Bayesian methods, educational data mining for programming courses, and healthcare analytics for infection control. She holds affiliations with ADAPT (FinTech research), ARC-SYM (complex systems modeling), and Lero (software engineering). Recent publications demonstrate cross-disciplinary applications, spanning cryptocurrency market analysis, hospital readmission prediction, and synthetic data generation for medical conditions. Work frequently employs machine learning, graph-based methods, and advanced statistical modeling. No information is available regarding awards, supervised students, or specific laboratory facilities.
Yalemisew M Abgaz is an Assistant Professor at Dublin City University's School of Computing within the Faculty of Engineering and Computing. He coordinates the university-wide Data Literacy and Analytics module and researches semantic web technologies, software engineering, NLP, and computational creativity. His publications demonstrate interdisciplinary approaches, including semantic enrichment of cultural heritage, microservices decomposition, educational technology, and bias in NLP. Recent work examines gender bias in Amharic language models and microcurriculum-as-a-service design. Abgaz leads the ChIA project applying semantic tools to cultural data at the Austrian Academy of Sciences and collaborates with Lero Research Centre on software architecture. He mentors PhD candidates in computer vision applications for cultural heritage and microservice vulnerability analysis.
Dr. Muhammad Salman Pathan is an Assistant Professor in the School of Computing at Dublin City University (DCU), part of the Faculty of Engineering and Computing. His academic journey includes a PhD in Software Engineering from Beijing University of Technology (2019), supported by the China Scholarship Council (CSC) scholarship, and a Marie Sklodowska-Curie COFUND Action fellowship (2020) at University College Dublin (UCD) as a Research Scientist. From 2022 to 2024, he was a Senior Postdoctoral Researcher and Team Lead on the EPA-funded CircAI project at Maynooth University. Education: PhD in Software Engineering, Beijing University of Technology (2019) Marie Curie Fellowship, University College Dublin (2020) Research Interests: Dr. Pathan focuses on AI applications in sustainability, digital health, telecommunications, and IoT security. His work bridges machine learning with real-world challenges, including weather forecasting, circular economy frameworks, and AI-driven solutions for agriculture and environmental protection. He has published over 40 peer-reviewed papers, achieving 600+ citations, and collaborates with industry partners like Irish Manufacturing Research and Circuleire. Publications & Impact: His recent work emphasizes AI’s role in sustainability, including digital twin technologies for circular economies and AI-enhanced agricultural productivity. He has also explored cybersecurity solutions for IoT systems, integrating blockchain and federated learning. Awards & Contributions: China Scholarship Council (CSC) Scholarship Marie Sklodowska-Curie COFUND Action Fellowship Guest Editor for journals like Electronics (MDPI) and Frontiers in Communications Teaching & Mentorship: He contributes to teaching and mentoring students at undergraduate and graduate levels, fostering academic and professional growth. His career also includes roles as a journal reviewer and conference organizer, advancing academic rigor in AI and communications. Labs & Collaborations: Central to his work is the CircAI project at Maynooth University, where he led efforts to apply AI for environmental sustainability. He continues to engage with interdisciplinary teams to address global challenges through innovative technical solutions.
Dr. Annalina Caputo is an Assistant Professor in the School of Computing at Dublin City University and Academic Lead for the part-time MSc in Artificial Intelligence program. Since 2022, she serves as Assistant Head for Research Management. She is a funded investigator in the ADAPT and I-Form research centres, leading the Proactive Experience & Agency challenge. Her research spans Natural Language Processing, Information Retrieval, and Machine Learning, with applications in personalization systems. Dr. Caputo holds a Ph.D. in Computer Science from the University of Bari Aldo Moro, where she researched Semantics and Information Retrieval. She previously held research positions at Trinity College Dublin as an EDGE COFUND Marie Curie Fellow and at the University of Bari. She has participated in numerous evaluation campaigns including CLEF, SemEval, and WSDM Cup. Her current research focuses on Intelligent Information Access, Text Representation, Temporal Dynamics in IR, Personalized Retrieval, Semantic IR, Quantum IR, Cross-Language Retrieval, Question Answering, and Recommender Systems in NLP and Additive Manufacturing contexts. Dr. Caputo serves as Guest Editor for the Special Issue on Knowledge Graphs for Search and Recommendation and is General Co-Chair for ECIR 2023. Her recent publications demonstrate strong focus on transformer-based recommender systems, NLP applications in healthcare/manufacturing, and interactive retrieval systems.
Dr. Luca Rossetto serves as Assistant Professor in the School of Computing within Dublin City University's Faculty of Engineering and Computing. His research focuses on advanced multimedia retrieval systems and interactive technologies. Primary research domains include multimedia information retrieval, virtual reality interfaces, and multimodal systems design. Recent work explores human-computer interaction paradigms for video retrieval systems and knowledge representation frameworks for large-scale multimedia datasets. Publications demonstrate consistent focus on retrieval system architecture and evaluation, with emerging emphasis on VR-based interfaces and multimodal learning techniques. Recent papers frequently address efficiency optimization and user-centered design in complex information systems. No awards or supervised students are documented. Laboratory affiliations include the vitrivr multimedia retrieval engine development team.
Prof. Gabriel-Miro Muntean is a Professor at the School of Electronic Engineering, Dublin City University (DCU), Ireland. He holds a Ph.D. (2003) from DCU and B.Eng./M.Sc. degrees in Software Engineering from Politehnica University of Timisoara, Romania. He co-directs the DCU Performance Engineering Laboratory and is a Principal Investigator with Insight and Lero National Research Centres. His research focuses on multimedia networking, wireless/energy-aware communications, and technology-enhanced learning. Education: B.Eng. Software Engineering (Politehnica University of Timisoara, 1996) M.Sc. Software Engineering (Politehnica University of Timisoara, 1997) Ph.D. Electronic Engineering (DCU, 2003) Research Interests: Quality-oriented adaptive multimedia streaming Energy-efficient networking Personalized learning technologies 5G/6G network architectures Edge computing optimization Publications & Grants: Over 450 papers, 4 books, and 26 book chapters (H-index=53) EU Horizon 2020 projects: Coordinator of NEWTON, Lead in TRACTION Awards: IEEE Fellow (202X) IEEE Broadcast Technology Society Fellow Advising & Labs: Supervised 25 PhD students and 15 postdocs Co-director of DCU Performance Engineering Lab
Patrick Healy serves as an Associate Professor in the Department of Computer Science & Information Systems within the Faculty of Science and Engineering at the University of Limerick. He is an active member of Lero – the Irish Software Research Centre , contributing to Ireland's national software research initiatives. His research spans Information Visualization, Graph Drawing, Combinatorial Optimization, and Routing/Scheduling problems. He specializes in developing algorithms for graph layout, table formatting, and upward planarity testing, with recent work expanding into machine learning robustness, medical AI diagnostics, and occlusion handling in computer vision. His fingerprint analysis reveals deep expertise in digraph theory (100%), planarity (76%), edge optimization (71%), and combinatorial optimization (51%). Current research trends show a significant shift toward applied AI since 2022, with 12 of his 15 most recent publications focusing on neural network robustness, medical diagnostics, and data augmentation techniques. Earlier work established foundations in graph theory and document engineering. He has supervised numerous research projects through Lero and maintains active collaborations across European institutions, particularly in software engineering and AI applications. His laboratory work centers on the Visualisation and Algorithm Design Group at UL, focusing on interpretable AI systems and robust visualization frameworks.
Nikola Nikolov is an Associate Professor in the Department of Computer Science & Information Systems at the University of Limerick. He holds memberships in the Centre for Research Training in Foundations of Data Science, the Data-Driven Computer Engineering Research Centre, and Lero – the Irish Research Centre for Software, reflecting his deep integration into Ireland's national research infrastructure. His research spans Machine Learning, Natural Language Processing, and Graph Drawing, with specialized expertise in deep learning architectures, matrix factorization techniques, and feature extraction methodologies. Current work focuses on multilingual NLP applications for social media analysis, convolutional neural network optimizations, and collaborative filtering systems, demonstrating consistent innovation across computational linguistics and graph theory domains. Analysis of his 2023-2025 publications reveals a dominant focus on combating online toxicity through advanced NLP systems for racism and hate speech detection across multiple languages, alongside significant contributions to computer vision efficiency and recommendation system architectures. His work bridges theoretical advancements with real-world applications in healthcare analytics and autonomous systems. Prof. Nikolov actively contributes to UN Sustainable Development Goals through data science applications while maintaining strong industry connections via research centres focused on software innovation and data-driven engineering solutions.
Chris Tanasescu is a Researcher at the Anderson Centre for Translation Research and Practice, University of Galway. His work bridges humanities and computation through creative research under the alias MARGENTO. He specializes in analyzing multilingual/multimodal datasets related to 19th-century Catholic publishing (PIETRA project) and develops computational methods for literary translation. Research interests include applying graph theory and NLP to translation studies, performance studies, and the intersection of algorithmic processes with creative writing. Notable works include US Poets Foreign Poets (2018), a computationally assembled poetry anthology, and an ongoing project on Belgian-Francophone poetry (forthcoming from Peter Lang). Active in the translation community as an Editor-at-Large for Asymptote Journal, he collaborates across academia and creative practice, exploring how computational methods can reshape literary analysis and cultural transmission.
Muhammad Haris Kaka Khel is a part-time lecturer at Atlantic Technological University's Department of Computing in Ireland while pursuing his Ph.D. in pedestrian trajectory prediction. His research focuses on developing adaptive systems that analyze human behavior, social interactions, and environmental dynamics to forecast multiple possible pedestrian paths using the PATHS framework. He works under supervisors Dr. Kevin Meehan and Dr. Paul Greaney at ATU Donegal, with additional guidance from Dr. Marion McAfee (ATU Sligo) and Dr. Sandra Moffet (Ulster University). B.S. in Electrical Engineering (Communication specialization) from UET Peshawar, Pakistan (2019) Research master's at University of Kuala Lumpur, Malaysia (completed 2022) with Erasmus exchange experience at Politecnico di Torino, Italy Ph.D. candidate at Atlantic Technological University (expected completion 2026) Research Interests Khel's work addresses critical gaps in pedestrian trajectory prediction by modeling multiple possible paths rather than single deterministic outcomes. This approach enhances robustness in dynamic environments like urban streets and public spaces, with applications in: Autonomous vehicle navigation safety Urban planning and walkability improvements Event crowd management systems Smart surveillance for anomaly detection Accessible navigation for visually impaired Public transportation optimization Teaching & Collaboration As a part-time lecturer at ATU Donegal, he contributes to computing education while maintaining external collaborations including: Sponsored research with Saudi Arabia's Deputyship for Research and Innovation Graduate research assistant role at University Kuala Lumpur-British Malaysian Institute Former intern at Center of Intelligent Systems and Networks Research
